| Incorporating prior domain knowledge into deep neural networks N Muralidhar, MR Islam, M Marwah, A Karpatne, N Ramakrishnan 2018 IEEE international conference on big data (big data), 36-45, 2018 | 223 | 2018 |
| Phynet: Physics guided neural networks for particle drag force prediction in assembly N Muralidhar, J Bu, Z Cao, L He, N Ramakrishnan, D Tafti, A Karpatne Proceedings of the 2020 SIAM International Conference on Data Mining, 559-567, 2020 | 67 | 2020 |
| Physics-guided deep learning for drag force prediction in dense fluid-particulate systems N Muralidhar, J Bu, Z Cao, L He, N Ramakrishnan, D Tafti, A Karpatne Big Data 8 (5), 431-449, 2020 | 43 | 2020 |
| Systems and methods for recommending temporally relevant news content using implicit feedback data N Muralidhar, HAN Eui-Hong Sam, H Rangwala US Patent 10,977,322, 2021 | 39 | 2021 |
| Steering a historical disease forecasting model under a pandemic: Case of flu and covid-19 A Rodríguez, N Muralidhar, B Adhikari, A Tabassum, N Ramakrishnan, ... Proceedings of the AAAI Conference on Artificial Intelligence 35 (6), 4855-4863, 2021 | 34 | 2021 |
| Contrastive graph convolutional networks for hardware Trojan detection in third party IP cores N Muralidhar, A Zubair, N Weidler, R Gerdes, N Ramakrishnan 2021 IEEE International Symposium on Hardware Oriented Security and Trust …, 2021 | 32 | 2021 |
| Deep learning methods for predicting fluid forces in dense particle suspensions NR Ashwin, Z Cao, N Muralidhar, D Tafti, A Karpatne Powder Technology 401, 117303, 2022 | 30 | 2022 |
| illiad: Intelligent invariant and anomaly detection in cyber-physical systems N Muralidhar, C Wang, N Self, M Momtazpour, K Nakayama, R Sharma, ... ACM Transactions on Intelligent Systems and Technology (TIST) 9 (3), 1-20, 2018 | 30 | 2018 |
| Physics-guided design and learning of neural networks for predicting drag force on particle suspensions in moving fluids N Muralidhar, J Bu, Z Cao, L He, N Ramakrishnan, D Tafti, A Karpatne arXiv preprint arXiv:1911.04240, 2019 | 27 | 2019 |
| Evaluation of FluSight influenza forecasting in the 2021–22 and 2022–23 seasons with a new target laboratory-confirmed influenza hospitalizations SM Mathis, AE Webber, TM León, EL Murray, M Sun, LA White, LC Brooks, ... Nature communications 15 (1), 6289, 2024 | 23 | 2024 |
| Large multi-modal models (LMMs) as universal foundation models for AI-native wireless systems S Xu, CK Thomas, O Hashash, N Muralidhar, W Saad, N Ramakrishnan IEEE Network, 2024 | 20 | 2024 |
| DyAt Nets: Dynamic Attention Networks for State Forecasting in Cyber-Physical Systems. N Muralidhar, S Muthiah, N Ramakrishnan IJCAI, 3180-3186, 2019 | 20 | 2019 |
| Using antipatterns to avoid mlops mistakes N Muralidhar, S Muthiah, P Butler, M Jain, Y Yu, K Burne, W Li, D Jones, ... arXiv preprint arXiv:2107.00079, 2021 | 15 | 2021 |
| Multivariate long-term state forecasting in cyber-physical systems: A sequence to sequence approach N Muralidhar, S Muthiah, K Nakayama, R Sharma, N Ramakrishnan 2019 IEEE International Conference on Big Data (Big Data), 543-552, 2019 | 14 | 2019 |
| Recommending temporally relevant news content from implicit feedback data N Muralidhar, H Rangwala, EHS Han 2015 IEEE 27th International Conference on Tools with Artificial …, 2015 | 14 | 2015 |
| Comparison of reduced order models based on dynamic mode decomposition and deep learning for predicting chaotic flow in a random arrangement of cylinders NA Raj, D Tafti, N Muralidhar Physics of Fluids 35 (7), 2023 | 10 | 2023 |
| Phyflow: Physics-guided deep learning for generating interpretable 3D flow fields N Muralidhar, J Bu, Z Cao, N Raj, N Ramakrishnan, D Tafti, A Karpatne 2021 IEEE International Conference on Data Mining (ICDM), 1246-1251, 2021 | 6 | 2021 |
| Cut-n-reveal: Time series segmentations with explanations N Muralidhar, A Tabassum, L Chen, S Chinthavali, N Ramakrishnan, ... ACM Transactions on Intelligent Systems and Technology (TIST) 11 (5), 1-26, 2020 | 6 | 2020 |
| Overcoming barriers to skill injection in language modeling: Case study in arithmetic M Sharma, N Muralidhar, N Ramakrishnan arXiv preprint arXiv:2211.02098, 2022 | 5 | 2022 |
| Detection of false data injection attacks in power systems using multiplex invariant networks and domain knowledge K Nakayama, C Jin, R Sharma, N Muralidhar US Patent 10,585,123, 2020 | 5 | 2020 |
Naren RamakrishnanThomas L. Phillips Professor, Virginia TechE-mail confirmado em cs.vt.edu